This study was conducted to investigate the effects of blended oils with an balanced n-6/n-3 polyunsaturated fatty acid (PUFA) ratio of 6:1 and unsaturated fatty acid/saturated fatty acid (UFA/SFA) ratio of 2.5:1 on growth performance and intestinal health in LPS-challenged piglets. One hundred and twenty piglets were selected and randomly assigned to two treatments (2% soybean oil or 2% blended oils). On d 28, the experiment was conducted as a 2 × 2 factorial arrangement of treatments including dietary treatment (2% soybean oil vs. 2% blended oil) and LPS challenge (saline vs. LPS). The results showed that the blended oils supplementation increased ADG and ADFI during 1-14 days (P < 0.05), and reduced feed to gain ratio in the whole experimental period (P < 0.05). In addition, the blended oils supplementation improved intestinal morphology, increased maltase and sucrase activities, and alleviated inflammation response in the intestine. Moreover, the blended oils supplementation increased proliferating cell nuclear antigen (PCNA) mRNA expression in jejunum and Ki67 mRNA expression in ileum (P < 0.05) in both saline-treated piglets and LPS-challenged piglets. The blended oils reduced C-myc and caspase-3 mRNA expressions and increased Axin2 and Cyclin d1 mRNA expressions after LPS challenge (P < 0.05). In conclusion, the blended oils can improve growth performance and promote intestinal health in piglets.

We present an experimental study of proton acceleration driven by femtosecond multi-PW lasers of three different prepulse parameters with the peak laser intensity of 1.2 × 1021 W/cm2 irradiating micrometre-thick metal foils. For 4-μm-thick copper foils, the highest-energy proton beam of 58.9 MeV is generated with the moderate-contrast laser, while the low-contrast or high-contrast lasers result in the lower proton cutoff energies. The one-dimensional hydrodynamic and two-dimensional particle-in-cell simulations indicate that the front preplasma of foils induced by the laser prepulse can enhance electron acceleration and in turn improve proton acceleration, while the rear preplasma will weaken the sheath field and be unfavourable for accelerating ions. For the case of the moderate contrast, the scale length of the front preplasma is long enough to generate high-temperature electrons compared to the high-contrast case, and the scale length of the rear preplasma is so short that the sheath field still remains strong compared with the low-contrast case, which is advantageous for generating high-energy protons. Meanwhile, a concrete map is theoretically given for accelerating higher-energy protons. This work extends the concept of the prepulse effect on target normal sheath acceleration (TNSA) to a wider range of laser parameters (multi-PW, 1021 W/cm2), representing an important step towards potential applications of TNSA-driven proton sources, especially considering that PW and even 10 PW laser facilities exist all around the world.

Community-acquired pneumonia (CAP) remains an important public-health problem, and the COVID-19 pandemic and non-pharmaceutical interventions (NPIs) may have altered its burden. This study aimed to provide updated CAP burden among adults in Shanghai from 2016–2023.We analysed 61,230 participants aged 20–74 years from the Shanghai Suburban Adult Cohort and Biobank. CAP episodes were ascertained via ICD codes and clinical diagnoses. We calculated incidence rates before, during, and after NPIs, conducted subgroup analyses by age, sex, comorbidity and lifestyle. We used Poisson regression to compare stages, and Cox models to identify risk factors. The Overall CAP incidence was 42.1 per 1,000 person–years (95% CI 41.3–42.8). Incidence declined during NPIs (24.2/1,000 py) and rose after NPIs (95.9/1,000 py). The inpatient-to-outpatient ratio increased to 10.1% during NPIs and fell to 5.7% post–NPI. Among those without underlying conditions, rates were 40.1, 20.1 and 73.6/1,000 py before, during and after NPIs. Incidence was higher in participants ≥60 years and in those with multiple comorbidities, especially respiratory diseases. CAP burden temporarily fell during NPIs but resurged post–NPI, notably among high–risk groups. These findings highlight the need for targeted preventive strategies and continued CAP surveillance in the post-pandemic era.

In view of the post-stroke finger contracture period, the patient’s muscle weakness causes the fingers to bend and not be extended, and the fingers are in a contracture state. A new hand rehabilitation exoskeleton with a cable and leaf spring hybrid drive is designed. The high-stiffness leaf spring helps the patient complete the extension movement, and the flexion and grasping movement is completed under the action of the cable. The exoskeleton combines the cable and the leaf spring in the driving form. It is flexible and can generate enough grasping force to meet daily activities. The workspace when wearing the exoskeleton is analyzed, and the simulation verifies that the exoskeleton has a high movement space. The stiffness of the finger module is analyzed to determine the appropriate size parameters of the leaf spring. The experimental prototype is built, and the structural performance test is carried out. A prosthetic hand model is made to simulate the hand of a patient without motor ability. The position control is carried out to complete the gesture experiment and grasping experiment, which verifies that the exoskeleton can meet the rehabilitation needs and daily grasping movements. Finally, a variety of performance parameters are designed to evaluate a variety of exoskeletons. The comparison shows that the exoskeleton in this paper has significant advantages, and the area coverage rate of the performance evaluation map can reach 70.4% of the ideal exoskeleton.

The “innovation championship” model has been instrumental in explaining policy innovations in China’s local governments, particularly at the provincial level. However, discrepancies between this model and real-world cases raise questions about its broader applicability. To address this, we employ a dichotomous framework (innovation generation/borrowing) and conduct multi-level quantitative analyses of government work reports. Our analysis suggests that between 2003 and 2022, most provincial innovations were driven by the championship model, which relies on central government recognition, while others were shaped by peer recognition mechanisms. Together, these form a “central and peer” (CP) model that prioritizes innovation generation while incorporating a degree of innovation borrowing. This CP model differentiates the innovation functions among provincial governments, which have formed a collective innovation network: pioneering provinces generate model policies, while others capitalize on these opportunities. Moreover, the extent of the central authority’s influence determines the relative importance of these two mechanisms.

To address the scarcity of data on compacted snow shear damage under complex conditions, unconfined shear tests were conducted in Northeast China. This study examined apparent shear strength variations with density (300–550 kg·m−3), temperature (−17.4°C to 0°C) and strain rate (1.3 × 10−5–3.8 × 10−2 s−1), complemented by discrete element method simulations of particle rearrangement and crack extension. The key findings include the following. (1) The apparent shear strength first increases but then decreases with increasing strain rate, increasing by 56% during ductile failure and decreasing by 97% during brittle failure. The form of damage transitions from ductile to brittle as deformation and crack expansion occur, with a critical strain rate of ∼10−4 s−1. (2) An increase in compacted snow density significantly enhances shear capacity and inhibits crack propagation; a density increase of 200 kg·m−3 can reduce transverse and longitudinal snow cracks by 10–20%. (3) Snow temperature influences bond strength, thereby affecting both the strength value and the size of deformation cracks. Snow temperature exhibits a negative correlation with apparent shear strength. This study is significant for understanding alpine snow layer shear damage mechanisms and useful for compacted snow pavement design.

The multiple-choice (MC) item format has been adapted to the cognitive diagnosis (CD) framework. Early approaches simply dichotomized the responses and analyzed them with a CD model for binary responses. Obviously, this strategy cannot exploit the additional diagnostic information provided by MC items. De la Torre’s (2009, Applied Psychological Measurement, 33, 163–183) MC-DINA model was the first for the explicit analysis of MC items. However, the q-vectors of the distractors were constrained to be nested within the key and each other, which imposes serious restrictions on item development. Relaxing the nestedness-constraint, comes at a price. First, distractors may become redundant: they do not improve the classification of examinees beyond the response options already available for an item. Second, undesirable diagnostic ambiguity can arise from distractors that are equally likely to be chosen by an examinee, but have distinct attribute profiles pointing at different diagnostic classifications. In this article, two criteria, plausible and proper, are developed for detecting these problematic cases. Two theorems that permit for the detection and amendment of improper and implausible items are presented. An R function serving this purpose is used in several practical applications. Results of simulation studies and real data analysis are also reported.

African swine fever (ASF) is a highly contagious animal disease caused by African swine fever virus (ASFV). It is listed by the World Organization for Animal Health (WOAH) as an animal disease subject to statutory reporting. ASFV, a large, enveloped double-stranded DNA virus with high genomic complexity, exhibits a case fatality rate of up to 100%, posing a significant threat to the global pig industry and food safety. To date, the absence of a safe commercial ASFV vaccine primarily stems from challenges in identifying immunogenic viral antigens, insufficient characterization of ASFV pathogenesis, and limited understanding of the virus’s immune evasion mechanisms. Here, we review the pathogenic characteristics (morphological structure, clinical symptoms, and epidemiological characteristics), molecular biological characteristics, and infection mechanism of ASFV, as well as the immune response mechanism, vaccine research, and the latest information on ASFV in other areas. This review will be in favour of understanding the current state of knowledge of ASF and developing effective vaccines to control this disease.

We show that for any integer $k\ge 1$ there exists an integer $t_0(k)$ such that, for integers $t, k_1, \ldots , k_{t+1}, n$ with $t\gt t_0(k)$, $\max \{k_1, \ldots , k_{t+1}\}\le k$, and $n \gt 2k(t+1)$, the following holds: If $F_i$ is a $k_i$-uniform hypergraph with vertex set $[n]$ and more than $ \binom{n}{k_i}-\binom{n-t}{k_i} - \binom{n-t-k}{k_i-1} + 1$ edges for all $i \in [t+1]$, then either $\{F_1,\ldots , F_{t+1}\}$ admits a rainbow matching of size $t+1$ or there exists $W\in \binom{[n]}{t}$ such that $W$ intersects $F_i$ for all $i\in [t+1]$. This may be viewed as a rainbow non-uniform extension of the classical Hilton-Milner theorem. We also show that the same holds for every $t$ and $n \gt 2k^3t$, generalizing a recent stability result of Frankl and Kupavskii on matchings to rainbow matchings.

This study uses a coupled lattice Boltzmann and discrete element method to perform interface-resolved simulations of turbulent channel flow laden with finite-size cylindrical particles. The aim is to investigate interactions between wall-bounded turbulence and non-spherical particles with sharp edges. The particle-to-fluid density ratio is unity and gravity is neglected. Comparative analyses are conducted among long (length-to-diameter aspect ratio 2), unit (1) and short ($ 1/2 $) cylinders, along with spheres and literature data for spheroids. Results reveal both shared and distinct dynamic behaviours of cylinders and their effects on turbulence modulation. Notably, disk-like short cylinders can remain trapped near the wall due to their flat faces aligning closely with it – a behaviour unique to particles with sharp edges. Long and unit cylinders, as well as spheres, preferentially accumulate in high-speed streaks, while short cylinders cluster in low-speed streaks, demonstrating a strong aspect-ratio effect. Near the wall, long cylinders align their axis with the streamwise direction, while short cylinders orient perpendicular to the wall. Rotationally, long cylinders primarily spin, whereas short ones predominantly tumble. These trends arise from orientation preferences and differences in axial and spanwise moments of inertia. Cylindrical particles increase wall drag compared with the single-phase case, with short cylinders causing the greatest enhancement due to strong near-wall accumulation. Overall, the influence of aspect ratio on particle dynamics and turbulence modulation is more pronounced for cylindrical particles than for spheroidal ones.

Previous research has mainly explored the relationship between bilingual language control and domain-general cognitive control through behavioral correlations, often revealing epiphenomenal links rather than causality. This study utilizes transcranial magnetic stimulation (TMS) to investigate the causal roles of the left inferior frontal gyrus (LIFG) and left middle temporal gyrus (LMTG) in 33 unbalanced Chinese-English bilinguals. Continuous theta burst stimulation was applied in separate sessions to decrease cortical excitability, with vertex stimulation as a control. LIFG stimulation significantly increased switching costs in nonverbal switching tasks, highlighting its role in domain-general cognitive control. LMTG stimulation did not affect switching or mixing costs in language or nonverbal switching tasks, suggesting no causal involvement, but it reduced reaction times (RTs) during language switching tasks, underscoring its specialization in language processing. These findings highlight distinctions between the neural mechanisms of bilingual language control and domain-general cognitive control, particularly in the LIFG.

Aerothermal issues in hypersonic transitional swept shock wave/boundary-layer interactions (SBLIs) are critical for the structural safety of high-speed vehicles but remain poorly understood. In this work, previously scarce, high-resolution heat transfer distributions of the hypersonic transitional swept SBLIs, are obtained from fast-responding temperature-sensitive paint (fast TSP) measurements. A series of $34^\circ$ compression ramps with sweep angles ranging from $0^\circ$ to $45^\circ$ are tested in a Mach 12.1 shock tunnel, with a unit Reynolds number of 3.0 $\times$ 10$^{6}$ m$^{-1}$. The fast TSP provides a global view of the three-dimensional aerothermal effects on the ramps, allowing in-depth analysis on the sweep effects and the symmetry of heat transfer. The time-averaged results reveal that the heat flux peak near reattachment shifts upstream with decreasing amplitude as the sweep angle increases, and a second peak emerges in the $45^\circ$ swept ramp due to a type V shock–shock interaction. Downstream of reattachment, the heat flux streaks induced by Görtler-like vortices weaken with increasing sweep angle, whereas their dominant projected wavelengths show little dependence on sweep angle or spanwise location. Away from the ramp’s leading side, the transition onset of the reattached boundary layer gradually approaches the reattachment point. Finally, a general quasi-conical aerothermal symmetry is identified upstream of reattachment, although spanwise variations in transition onset, shock–shock interaction and heat flux streaks are found to disrupt this symmetry downstream of reattachment with varying degrees.

Computer vision–based precision weed control has proven effective in reducing herbicide usage, lowering weed management costs, and enhancing sustainability in modern agriculture. However, developing deep learning models remains challenging due to the effort required for weed dataset annotation and the difficulty of identifying weeds at different stages and densities in complex field conditions. To address these challenges, this study introduces an indirect weed detection method that combines deep learning and image processing techniques. The proposed approach first employs an object detection network to identify and label crops within the images. Subsequently, image processing techniques are applied to segment the remaining green pixels, thereby enabling indirect detection of weeds. Furthermore, a novel detection network—CD-YOLOv10n (You Only Look Once version 10 nano)—was developed based on the YOLOv10 framework to optimize computational efficiency. Redesigning the backbone (C2f-DBB) and integrating an optimized upsampling module (DySample) permitted the network to achieve higher detection accuracy while maintaining a lightweight structure. Specifically, the model achieved a mean average precision (mAP50) of 98.1%, which is a 1.4% percentage-point increase compared with the YOLOv10n baseline, a relevant improvement given the already strong baseline performance. At the same time, compared with YOLOv10n, its GFLOPs (giga floating-point operations per second) were reduced by 22.62%, and the number of parameters decreased by 15.87%. These innovations make CD-YOLOv10n highly suitable for deployment on resource-constrained platforms.

We consider a class of sequence $c(n)$ with the following asymptotic form:

$$ \begin{align*}c(n) \sim \frac C{n^\kappa} \exp\left(\sum_{\lambda\in\mathcal S}A_\lambda n^\lambda \right) \sum_{\mu\in\mathcal T} \frac{\beta_\mu}{n^\mu} \qquad (n \to \infty).\end{align*} $$

$c(n)$

$c(n)$

$\ell $

$S_n$

$\mathfrak {su}(3)$

$\mathfrak {so}(5),$